· Highlights how Artificial Intelligence and Machine Learning techniques are used in the Thermal Spray industry to predict future research directions · Sheds light on Artificial Intelligence’s versatility, revealing its applicability in solving problems related to conventional simulation and numeric modeling techniques · Combines automated technologies with expert machines to show several advantages, including decreased error and greater accuracy in judgment, and prediction, enhanced efficiency, reduced time consumed, and lower costs · Discusses how certain barriers are preventing the successfully implementing of Artificial Intelligence in the Thermal Spray industry Looks at how training and validating more models with microstructural features of deposited coating will be the center point to grooming this technology in the future · Offers a thorough analysis of the digital technologies available for modeling and achieving high-performance coatings including giving Artificial intelligence-related models like ANN and CNN more attention
Microbe-Assisted Phytoremediation of Environmental Pollutants: Recent Advances and Challenges provides comprehensive information on the principles and practical knowledge of microbe-assisted phytoremediation of organic and inorganic pollutants for environmental safety. This book describes the physiological, biochemical, microbiological, and molecular basis of microbe-assisted phytoremediation and contains many relevant topics to fill the gaps in developing an understanding of microbe-assisted phytoremediation of environmental pollutants. The book provides state-of-the-art knowledge on fundamental, practical, and purposeful utilization of plant-associated bacteria (plant growth-promoting rhizobacteria [PGPR] and endophytes) and arbuscular mycorrhizal fungi for plant-growth promotion and enhanced phytoremediation of environmental pollutants in the contaminated matrix. Features: Provides a state-of-the-art overview of microbe-assisted phytoremediation Emphasizes the roles of PGPR, endophytes, and mycorrhizal fungi in assisted phytoremediation Elucidates biochemical and molecular mechanisms of microbe-assisted phytoremediation Details field studies and success stories of microbe-assisted phytoremediation Explores advances, challenges, and future directions in microbe-assisted phytoremediation The book serves as a valuable resource for researchers, ecotoxicologists, environmental scientists and engineers, environmental microbiologists and biotechnologists, environmental health and risk scientists, environmental science managers and administrators, remediation practitioners, environmental policymakers, and students at the postgraduate and doctoral levels in the relevant fields who wish to work on microbe-assisted phytoremediation of pollutants for environmental safety and sustainability.
· Highlights how Artificial Intelligence and Machine Learning techniques are used in the Thermal Spray industry to predict future research directions · Sheds light on Artificial Intelligence’s versatility, revealing its applicability in solving problems related to conventional simulation and numeric modeling techniques · Combines automated technologies with expert machines to show several advantages, including decreased error and greater accuracy in judgment, and prediction, enhanced efficiency, reduced time consumed, and lower costs · Discusses how certain barriers are preventing the successfully implementing of Artificial Intelligence in the Thermal Spray industry Looks at how training and validating more models with microstructural features of deposited coating will be the center point to grooming this technology in the future · Offers a thorough analysis of the digital technologies available for modeling and achieving high-performance coatings including giving Artificial intelligence-related models like ANN and CNN more attention
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